Urban Rail Transit Passenger Travel Characteristics Mining and Passenger Classification Based on Workplace-residence Relationship
Journal Title: Urban Mass Transit - Year 2024, Vol 27, Issue 8
Abstract
Objective When mining travel characteristics from urban rail transit travel trajectory data, passenger travel activity patterns are found closely related to the stations near their residence and workplace. This is reflected in their travel trajectories by fixed boarding/alighting routes and concentrated entry/exit stations. Meanwhile, passenger travel trajectories associated with residence and workplace exhibit certain fluctuations, and the travel data strongly related to workplace-residence often differ significantly from other travel data. To accurately extract passenger travel trajectory characteristics, it is essential to clarify the residence-workplace relationship within urban rail transit passenger travel data. Method A mechanism for mining travel characteristics and classifying passengers based on residence-workplace relationship is proposed. The preliminary workplace-residence judgments are formed by identifying the hotspots of passenger trajectory activities related to residence, workplace and social activity locations. Then, the spatio-temporal patterns strongly associated with workplace-residence are explored. A K-means clustering algorithm extracted on the basis of passenger travel trajectory characteristic values is used to cluster passengers according to their residence-workplace judgment, resulting in a passenger classification method that precisely matches the passenger travel characteristics. Result & Conclusion Simulation validation results indicate that passengers with clearly defined residence-workplace relationship exhibit four distinct travel patterns of two-point, two-point-two-line, three-point, and multi-point. These travel pattern classification results make up a crucial technical foundation for constructing detailed passenger profiles and developing intelligent security check strategies.
Authors and Affiliations
Qi ZHOU, Lu GONG, Mingchen MA, Shousheng SUN, Qingqing CHANG
Keywords
Related Articles
- EP ID EP742690
- DOI 10.16037/j.1007-869x.2024.08.019
- Views 16
- Downloads 0
Causes and Countermeasures of Train Emergency Braking Failures under DRB Turn-back Mode on Xi’an Metro Line 14
Objective Under the DRB (driverless return button) mode on Xi’an Metro Line 14, the train emergency braking will occur after the train automatically switching its head car on the turn-back line, resulting in the train tu...
Simulation and Evaluation Model of Operation Delay Adjustment Plan for Urban Rail Transit Express and Local Trains
Objective Making a reasonable train delay adjustment plan is one of the key tasks to ensure the safe and reliable operation of urban rail transit lines. For those lines with express and local trains running on, it is nec...
Reasonable Energy Consumption Correction Method for Ventilation and Air-conditioning of Platform Screen Door Metro Stations in China
Objective In view of the continuous growth of energy consumption in metro stations, in order to accurately evaluate their current energy consumption level, tap energy conservation potential and promote energy conservatio...
Intelligent Detection System for Metro Tunnel Lining Defects Based on Deep Learning Method
Objective The main defects on metro tunnel inner wall are cracks and water seepage. Current detection methods based on manual and semi-automatic equipment have problems such as high intensity, low efficiency, and low rel...
Train Speed Measurement Approach Based on Wheel-axle Creep Rate Detection
Objective In urban rail transit systems, train velocity measuring and positioning technology offers critical information to many applications such as train autonomous driving, collision avoidance, dispatching and directi...